Size distribution estimation of stone fragments via digital image processing

Abstract

Precise statistics play a key role in the management of systems and processes. For instance, having knowledge about size distribution of stone fragments in a mining factory can allow suitable choosing of the diameter of a sieve or designing of a better crusher, hence optimizing the production line. This paper describes and compares three image-based techniques that statistically estimate stone size distribution. The techniques are watershed, granulometry and area boundary. Results show that in many mining stone factories due to identical stone texture, granulometry is a good replacement for edge detection based methods. An important point about granulometry is that its results are very qualitative; it cannot determine the exact number of stone fragments, but it can superlatively distinguish size distribution of objects in real images including objects with different textures, disparity and overlapping. © 2010 Springer-Verlag.